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Kick Control: Using the Attracting States Arising Within the Sensorimotor Loop of Self-Organized Robots as Motor Primitives

机译:脚踢控制:使用自组织机器人的感觉运动环中产生的吸引状态作为运动原语

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摘要

Self-organized robots may develop attracting states within the sensorimotor loop, that is within the phase space of neural activity, body and environmental variables. Fixpoints, limit cycles and chaotic attractors correspond in this setting to a non-moving robot, to directed, and to irregular locomotion respectively. Short higher-order control commands may hence be used to kick the system from one self-organized attractor robustly into the basin of attraction of a different attractor, a concept termed here as kick control. The individual sensorimotor states serve in this context as highly compliant motor primitives. We study different implementations of kick control for the case of simulated and real-world wheeled robots, for which the dynamics of the distinct wheels is generated independently by local feedback loops. The feedback loops are mediated by rate-encoding neurons disposing exclusively of propriosensoric inputs in terms of projections of the actual rotational angle of the wheel. The changes of the neural activity are then transmitted into a rotational motion by a simulated transmission rod akin to the transmission rods used for steam locomotives. We find that the self-organized attractor landscape may be morphed both by higher-level control signals, in the spirit of kick control, and by interacting with the environment. Bumping against a wall destroys the limit cycle corresponding to forward motion, with the consequence that the dynamical variables are then attracted in phase space by the limit cycle corresponding to backward moving. The robot, which does not dispose of any distance or contact sensors, hence reverses direction autonomously.
机译:自组织的机器人可能会在感觉运动回路内(即神经活动,身体和环境变量的相空间内)形成吸引状态。在此设置中,固定点,极限环和混沌吸引子分别对应于不移动的机器人,定向的机器人和不规则的运动。因此,可以使用短的高阶控制命令将系统从一个自组织的吸引子稳固地踢到另一个吸引子的吸引盆中,该概念在这里被称为反冲控制。在这种情况下,各个感觉运动状态充当高度顺应性的运动原语。我们针对模拟和现实的轮式机器人研究了脚蹬控制的不同实现,对于这种情况,不同车轮的动力学是通过局部反馈回路独立生成的。反馈环由速率编码神经元介导,该速率编码神经元专门根据车轮实际旋转角度的投影来布置本体感测输入。然后,神经活动的变化通过类似于用于蒸汽机车的传动杆的模拟传动杆传递为旋转运动。我们发现,根据踢球控制的精神以及与环境的交互作用,高层控制信号可能会使自组织吸引子景观变形。撞到墙上会破坏与向前运动相对应的极限循环,结果是,动态变量随后会被与向后运动相对应的极限循环吸引到相空间中。机器人不会放置任何距离或接触传感器,因此会自动反转方向。

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